class_docstr: VectorizedDistance class represents a distance that is calculated in a vectorized way. This means
  that instead of going through every pair and explicitly calculating its distance, VectorizedDistance
  uses the entire vectors to compare to each other in a single operation.
  
  Parameters
  ----------
  distance_function : Callable[[np.ndarray, np.ndarray], np.ndarray]
      Distance function used to determine the distances between new candidates and objects.
      This function should take 2 input arguments, the first being a `np.ndarray` and the second
      `np.ndarray`. It has to return a `np.ndarray` with the distance matrix it calculates.
docstr: Method that computes the pairwise distances between new candidates and objects.
  It is intended to use the entire vectors to compare to each other in a single operation.
  
  Parameters
  ----------
  stacked_candidates : np.ndarray
      np.ndarray containing a stack of candidates to be compared with the stacked_objects.
  stacked_objects : np.ndarray
      np.ndarray containing a stack of objects to be compared with the stacked_objects.
  
  Returns
  -------
  np.ndarray
      A matrix containing the distances between objects and candidates.
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code: def _compute_distance(
      self, stacked_candidates: np.ndarray, stacked_objects: np.ndarray
  ) -> np.ndarray:
      """
      Method that computes the pairwise distances between new candidates and objects.
      It is intended to use the entire vectors to compare to each other in a single operation.
  
      Parameters
      ----------
      stacked_candidates : np.ndarray
          np.ndarray containing a stack of candidates to be compared with the stacked_objects.
      stacked_objects : np.ndarray
          np.ndarray containing a stack of objects to be compared with the stacked_objects.
  
      Returns
      -------
      np.ndarray
          A matrix containing the distances between objects and candidates.
      """
      return self.distance_function(stacked_candidates, stacked_objects)
  
imports: from abc import ABC, abstractmethod
  from functools import partial
  from logging import warning
  from typing import TYPE_CHECKING, Callable, List, Optional, Sequence, Union
  import numpy
  from scipy.spatial.distance import cdist
label_desc: Use image node_id 3 for calling the VectorizedDistance obj's underlying member method code with example usage: obj._compute_distance(stacked_candidates, stacked_objects) and returns: self